Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/xyzbit/AI-CodingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/xyzbit/ai-coding/p-story-analysis)<a href="https://agentmods.dev/rules/xyzbit/ai-coding/p-story-analysis"><img src="https://agentmods.dev/badge/rules/xyzbit/ai-coding/p-story-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/xyzbit/ai-coding/p-story-analysis"><img src="https://agentmods.dev/badge/rules/xyzbit/ai-coding/p-story-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00005 | $0.00650 |
| Opus 5.5 | $0.00002 | $0.00260 |
| Sonnet 5.5 | $0.00001 | $0.00130 |
| Haiku 4.5 | $0.00001 | $0.00065 |
Grade A, and why
p-story-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
需求分析规则 (Story Analysis Guidelines)
规则目的
本规则旨在指导需求分析过程，确保需求的完整性、准确性和可执行性。
触发条件
当遇到以下情况时，应执行本规则：
- 收到新的需求文档或需求变更
- 需要进行需求分析和确认
- 需要进行技术可行性评估
核心步骤
1. 需求收集与理解
-
必要信息收集
- 业务背景和目标
- 核心业务流程
- 功能需求清单
- 非功能性需求（性能、安全等）
- 约束条件和限制
-
关键指标确认
- 业务指标（如转化率、使用率）
- 技术指标（如响应时间、并发量）
- 质量指标（如可用性、稳定性）
2. 需求分析流程
-
需求分解
1. 将大需求拆分为可独立交付的小功能点 2. 识别功能点之间的依赖关系 3. 确定功能点的优先级 -
技术可行性评估
1. 评估现有系统架构的支持程度 2. 识别技术难点和风险点
3. 沟通确认机制
-
必须确认项
1. 模糊描述必须量化（例如： - "提升性能" → "API响应时间≤200ms" - "优化体验" → "操作步骤减少50%"） 2. 技术方案的风险点和应对措施 3. 资源需求和时间预估 -
输出文档要求
《需求确认清单》，包含： - 功能点列表 - 具体指标要求 - 验收标准 - 假设条件
4. 风险管理
- 风险评估维度
1. 技术风险 - 技术可行性 - 性能瓶颈 - 安全隐患 2. 业务风险 - 需求变更可能性 - 业务规则冲突 - 用户接受度
验收标准
- 需求文档完整性检查表
- 技术方案评审通过
- 产品方（用户）确认签字
- 风险评估报告评审通过
注意事项
- 严禁对需求进行主观臆断，
- 所有关键决策必须进行确认
- 定期同步需求变更和进展状态
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 87 lines · 5 tokens per session scan A 1445e22ff270
p-story-analysis is a cursor rule published in the GitHub repository xyzbit/AI-Coding (21 stars, last pushed 12mo ago), licensed Apache-2.0. It adds 5 tokens to every session and 650 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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